Research & Initiatives

Design and implementation of integrable sensing and data analytical methods

Most mineral processing and extractive metallurgical industries are characterized by large volumes of waste due to the lack of proper sensor investment and data analytics coupled with process integration. Our research in this area involves application of existing and newly developed sensors together with machine learning and data science techniques to niche areas towards addressing process critical challenges. Maximization of each unit operation for overall integrated value chain financial performance and process sustainability is key.

 

Engineering advanced, future-driven, efficacious valued metal extraction routes

Rising metal demands for well-known, existing and newly desired commodities require development of well-targeted, efficacious metal extraction routes. As existing deposits get deeper, traditional technologies fail to profitably extract the valued metals, requiring engineering of advanced techniques and processing pathways. Our research in this area focuses on precious and base metals, and critical minerals.

 

Uncovering performance-critical limitations in process streams

Not all poor process performance requires implementation of new methods. In some specific cases, eliminating the bottleneck through fundamental studies is required. Under this category, we investigate different processing routes in discovery of fundamental, complex interactions leading to specific process performance. This includes designing an early response strategy towards changing the fate of the plant to profitable outcomes.